Numerical modeling of LiDAR-based geological model for landslide analysis

Hu, Haiyuan; Fernández-Steeger, Tomás Manuel; Dong, Mei; Azzam, Rafig

doi:10.1016/j.autcon.2012.03.001

Cited by 35 publications

(16 citation statements)

References 12 publications

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“…An effective approach to landslide forecasting should go through the integration of RS techniques into spatial sensors networks [234], which are able to gather various kinds of information from contact sensors, geotechnical sensors, and multi-platform RS techniques. Several authors followed this approach: RS and geotechnical instruments are employed to define the surface movements, while geophysical methodologies are applied to characterize the subsurface [7,286,287]. The use of multi-sensor data needs the development of an interface able to merge and integrate all information.…”

Section: Discussionmentioning

confidence: 99%

Remote Sensing for Landslide Investigations: An Overview of Recent Achievements and Perspectives

et al. 2014

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Landslides represent major natural hazards, which cause every year significant loss of lives and damages to buildings, properties and lifelines. In the last decades, a significant increase in landslide frequency took place, in concomitance to climate change and the expansion of urbanized areas. Remote sensing techniques represent a powerful tool for landslide investigation: applications are traditionally divided into three main classes, although this subdivision has some limitations and borders are sometimes fuzzy. The first class comprehends techniques for landslide recognition, i.e., the mapping of past or active slope failures. The second regards landslide monitoring, which entails both ground deformation measurement and the analysis of any other changes along time (e.g., land use, vegetation cover). The third class groups methods for landslide hazard analysis and forecasting. The aim of this paper is to give an overview on the applications of remote-sensing techniques for the three categories of landslide investigations, focusing on the achievements of the last decade, being that previous studies have already been exhaustively reviewed in the existing literature. At the end of the paper, a new classification of remote-sensing techniques that may be pertinently adopted for investigating specific typologies of soil and rock slope failures is proposed.

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Section: Discussionmentioning

confidence: 99%

Remote Sensing for Landslide Investigations: An Overview of Recent Achievements and Perspectives

et al. 2014

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“…Various researchers have investigated the effect of DEM (Digital Elevation Model) resolution on landscape representation [29][30][31]. These data were combined with landslide observations and landslide models [32]. The benefits of laser scanning are the ability to quickly generate data of an object surface, easy leveling process, and fewer human errors [33].…”

Section: Advances In Meteorologymentioning

confidence: 99%

Numerical Simulation of the Topographical Change in Korea Mountain Area by Intense Rainfall and Consequential Debris Flow

Jun

2016

Advances in Meteorology

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The objectives of this study are to simulate the topographical changes associated with rainfall and the consequential debris flow using terrestrial LiDAR (Light Detection And Ranging). Three rainfall events between July 9 and July 14, 2009, triggered a number of debris flows at Jecheon County in Korea. Rain fell at a rate of 64 mm/h, producing 400 mm of total accumulation during this period. Tank simulation model for SWI (Soil Water Index) estimated the water stored beneath the ground and debris flow occurrence in study area. For the LiDAR (Light Detection and Ranging) survey, the terrestrial laser scanning system RIEGL LMS-Z390i consists of an accurate and fast 3D scanner, associated RTK GPS system. The DEM derived from LiDAR enabled the debris flow to be mapped and analyzed in great detail. The estimated affected area and erosion/deposition volumes by debris flow were compared with two-dimensional numerical simulation. The simulation results were sufficiently in good agreement with the debris flow track, and a success rate of over 90% was achieved with a simulation time of 300 s. A comparison of the simulated and surveyed results based on deposition volume yields a success rate of over 97% with 350 s of simulation time.

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“…These numerical methods have recently been incorporated with new technologies to generate suitable 2D/3D models for analysis. For example, LiDAR technology was used to generate a 3D model, upon which 2D FEMs were built to estimate the safety factor at specific sites (Hu et al 2012). TLS technology was applied to reconstruct the geometry of slopes in Italy, and the generated 3D model was used to simulate the landslide and rockfall processes (Marsella et al 2015).…”

Section: Introductionmentioning

confidence: 99%

Three-dimensional slope stability analysis using laser scanning and numerical simulation

Wang

Guiling

et al. 2017

Geomatics, Natural Hazards and Risk

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Detailed surface topography is important when analyzing the stability of slopes. Recent advances in new technologies such as interferometric synthetic aperture radar and light detection and ranging have allowed us to obtain high-precision profiles of distant landscapes and objects including detailed slope information for three-dimensional (3D) slope stability analysis. However, techniques of reconstructing 3D numerical models from scanned data of slope geometry have not been well investigated or tested. This paper proposes a comprehensive approach that integrates laser scanning and finite element method for slope stability analysis, particularly failure prediction under precipitation scenarios. The methodology is applied to a slope in the Wenchuan earthquake-stricken mountainous region that failed in 2013, triggered by severe rainfall. The modelling results show that the surface sampling resolution can affect the prediction accuracy of the potential failure zones. When constructing the slope model, the selected surface grid should be fine enough to capture the important topographic features of the slope while minimizing computation demand. This paper confirms that the proposed method can be successfully used to identify the potential failure zones of the investigated slope under severe rainfall conditions.

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Numerical modeling of LiDAR-based geological model for landslide analysis

Cited by 35 publications

References 12 publications

Remote Sensing for Landslide Investigations: An Overview of Recent Achievements and Perspectives

Remote Sensing for Landslide Investigations: An Overview of Recent Achievements and Perspectives

Numerical Simulation of the Topographical Change in Korea Mountain Area by Intense Rainfall and Consequential Debris Flow

Three-dimensional slope stability analysis using laser scanning and numerical simulation

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